Ph. D in End to End IoT Security: Authentication, Vulnerability Exploration and Data Analysis
I completed my Ph.D. in IoT Security at the University of Technology Sydney (UTS) in collaboration with CSIRO. My thesis title is “End-to-End IoT Security: Authentication, vulnerability Exploration, and Data Analysis with machine learning.” I am working as a Research Associate in the “Finding the vulnerability of routing protocols” project at the University of New South Wales (UNSW) since 2021. Also, I am one of the members of the IFCYBER research community at UNSW. I worked as a casual academic from 2018 to mid-2021 at the University of Technology Sydney (UTS). I demonstrated my expertise and hands-on experience in Data Science, Cyber Security - IoT Security, Authentication, and Vulnerability Exploration through my publications. Demonstrated the data analysis capability in network traffic data set using machine learning algorithms and deep learning-clustering algorithms (Collecting the network traffic data, cleaning the data, analyzing the data, building the machine learning model, Testing the built-up models, monitoring the performances of those models, and visualizing the best model). The corresponding research paper has been published in a Q1-ranked journal.
Current research project is vulnerability discovery through fuzzing for network protocols.
Previous research projects:
Project 1: Exploring the vulnerability of the application layer protocol (CoAP)
Project 2: Network Security---Authentication of WSN (Wireless Sensor Network)
Project 3: Intelligent anomaly detection for large network traffic with Optimized Deep Clustering (ODC) algorithm